Flood Protection and Runoff Quantification Based on Two Free Global Digital Elevation Models: A Case of Wadi Qaws, Jeddah, Saudi Arabia

Global 30 m Digital Elevation Models (GDEMs) generated by Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Shuttle Radar Topography Mission (SRTM) have been widely adopted to assess flood risk. Nonetheless, the performance and reliability of flood risk models in areas with complex terrain have not been thoroughly evaluated. Using two GDEMs, this study assesses how resolution affects the outflow hydrograph of Wadi Qaws, Saudi Arabia. The study evaluated the effectiveness of existing dams in the Wadi Qaws watershed using hydrograph analysis. Hydrologic models were developed using a Geographic Information System (GIS), the Watershed Modeling System (WMS), and the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS). These models were designed to simulate flood behavior under projected conditions. The delineated area was 73.1 km² with SRTM and 66.8 km² with ASTER, resulting in a 9% difference. Consequently, for the 100-year return period, the peak discharge at the outlet of Wadi Qaws was 581.3 m³/s using the SRTM and 559.7 m³/s using the ASTER, with a percentage difference of 3.7%. These values significantly decreased after the constructed dams were included, with peak discharges of 64.7 m³/s for the 30-m SRTM and 77.3 m³/s for the 30-m ASTER. The 30-m ASTER was unable to precisely delineate the basin of dam 2, resulting in a significantly reduced storage volume, although the differences in drainage area and peak discharge were negligible in the mountain area. Nonetheless, when the urban coastal area downstream of Wadi Qaws was included, the two DEMs exhibited substantial differences in stream networks, delineated area, peak discharges, and runoff volumes. Differences in watershed delineation and discharge estimates point to potential risks in infrastructure under- or over-design, especially where dam performance assessments depend on terrain accuracy. A better understanding of the variability in performance and impact between GDEM products can support more informed decisions about model reliability.